EC 613: Advanced Topics in Financial Econometrics[1.4cm ... · 9/27/2012 · Angi R osch angi at angi-stat dot com The slides were produced using LATEX and R (the R project; website:

EC 613:Advanced Topics in Financial Econometrics

FEC 514:Applications in Financial Modeling

Harald Schmidbauer

c© Harald Schmidbauer & Angi Rosch, 2012

About These Slides

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Harald Schmidbauer harald at hs-stat dot comAngi Rosch angi at angi-stat dot com

• The slides were produced using LATEX and R (the R project; website: www.R-project.org) on a GNU/Linux system.

• R files used for this course are available upon request.

c© Harald Schmidbauer & Angi Rosch, 2012 About these slides 2/32

Some Projects

From Our Recent Research

c© Harald Schmidbauer & Angi Rosch, 2012 Recent Research Projects 3/32

Recent (and ongoing) research projects.

The following slides give an outline of four projects.

• Project 1: Green segmentation: a cross-national study

(with Barıs Yılmazsoy & Angi Rosch)

• Project 2: Algorithmic trading

(with Angi Rosch, Tolga Sezer & Vehbi Sinan Tunalıoglu)

• Project 3: Festivals and Gold Prices

(with Angi Rosch)

• Project 4: Population Dynamics With Leslie-Type Models

(with Angi Rosch & Narod Erkol)

• Project 5: OPEC Announcements and Oil Price Volatility

(with Angi Rosch)

c© Harald Schmidbauer & Angi Rosch, 2012 Recent Research Projects 4/32

Project 1:

Green Segmentation: A Cross-National Study

Some aspects.

• world facing environmental challenges

• business consequences

• shift in consumer attitude and preferences

• understanding the “green” consumer is important

• key concepts: attitudes, behavioural intentions

• theory of Reasoned Action:

attitudes ⇒ behavioural intentions ⇒ actual behaviour

• relationship between green attitudes and green behaviour:

no agreement in literature

c© Harald Schmidbauer & Angi Rosch, 2012 From Our Recent Research: Project 1 5/32

Project 1:


The questionnaire: Attitude items.

strongly agree / agree / indifferent / don’t agree / don’t agree at all

• Tenor, basic attitudes: A1, A4, A9

too much trouble; not too late to save the environment; natural resources are

scarce

• Emotional concern: A2, A5, A8

responsible for global warming; frustrated with industies polluting; frightened

with chemicals in food

• Scepticism: A3, A6, A7

job loss; green trend is marketing gimmick; benefits of consumer products

more important


Project 1:


The questionnaire: Behaviour items.

always / mostly / sometimes / rarely / never

• Daily behaviour: B1, B3, B8, B9

using public transport; re-usable bags; energy-saving light bulbs; recycling

• Consumption: B5, B6

products with less packaging; buying more expensive “greener alternative”

• Environmental activism: B2, B4, B7

advising others; participation in meetings; reading about environmental issues


Project 1:


Data & Analysis.

• Data (convenience sample) from China (395), Germany (360),

Turkey (660)

• students enrolled in business-related programmes in

private/public universities

• “Split the difference”-method used to eliminate gender effect

• For each country: four segments (clusters) obtained using “pam”


Project 1:


Characterizing clusters.

● ●

●

●

●

cndetr

1

1

1

22

2

3

3

34

4

4

attitude

beha

viou

r


Project 1:


Managerial Implications.

• Focus on segment-specific customer expectations.

• Incentive for shifting customers to “greener segment”?

• “Positive marketing”: parties exchange value such that they are

better off

• Environmental attitude and purchase channel choice???


Project 2:

Algorithmic Trading

Algorithmic trading.

• Can we combine simple trading rules to generate profit?

• Example: e-$ trading.

– Trading every 5 minutes.

– Use 2 days’ data to construct a trading rule.

– Use this rule for the next day.


Project 2:

Algorithmic Trading

A sequence of trading signals.


Project 2:

Algorithmic Trading

How to obtain complex trading rules?

• Genetic algorithm: based on

– cross-over

– mutation

– reproduction

• Example of a program:

(IF TR1 = “buy!”) AND NOT

((TR2 = “sell!”) OR (TR3 = “sell!”)

)THEN “buy!”


Project 2:

Algorithmic Trading

Creating a Program.

program 1...

program N

p1...

pM

FC

FC

final program

pool population

No!

Yes!

Yes!

No!

currentfittest

terminalcondition?

fitter?

genetic operations:

• cross-over

• mutation

• reproduction


Project 2:

Algorithmic Trading

Keywords.

• data-snooping bias

• robustness

• time series bootstrap

• tick data


Project 3: Festivals and Gold Prices

A festival calendar.

2012201120102009200820072006200520042003200220012000199919981997199619951994199319921991

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Aks

haya

Trit

iya

Chi

nese

New

Yea

r

Diw

ali

Dus

sehr

a

Eas

ter

Eid

al−

Adh

a

Ram

adan

Eid

Chr

istm

as

. . . and their impact on daily returns on gold?



Gold prices.

050

010

0015

0020

00

US

D/o

z.

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Akshaya TritiyaChinese New YearChristmasDussehraRamadan Eid



Daily returns on prices.

−8

−6

−4

−2

02

46

8

daily

ret

urn

in p

erce

nt

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Akshaya TritiyaChinese New YearChristmasDussehraRamadan Eid



The model: regression and GARCH.

rt = c+ νt√ht = c+ εt (1)

νt = ηt +∑i

bi dit (2)

ht = α0 + α1 ε2t−1 + β ht−1 +

∑i

γi dit (3)

• Summation is over festivals.

• (rt): series of daily returns on gold price

• (dit): (extended) dummy variables for festival i

• (ηt): Gaussian white noise with var(νt) = 1

• bi, γi: parameters quantifying the impact of festival i



Some findings (details not shown here).

impact on. . .festival expectation volatility

Akshaya Tritiya * *

Chinese New Year *

Christmas * *

Diwali

Dussehra *

Easter *

Eid al-Adha *

Ramadan Eid * *


Project 4:

Population Dynamics With Leslie-Type Models

The classical Leslie model.

• Leslie model:

a discrete, age-structured model of population growth

• time-constant age-specific fertility and mortality rates

• population is closed to migration

• only females considered

• three 15-year intervals of age covering ages 0 to 45


Project 4:


The classical Leslie model.

• Equation of the Leslie model: n1,t

n2,t

n3,t

=

f1 f2 f3p1 0 0

0 p2 0

·

n1,t−1

n2,t−1

n3,t−1

~nt = M · ~nt−1


Project 4:


A Leslie-type model for a population with constant immigration.

n1,t

n2,t

n3,t

n∗1,t

n∗2,t

n∗3,t

R

=

f1 f2 f3 f∗1 f∗2 f∗3 0

p1 0 0 0 0 0 0

0 p2 0 0 0 0 0

0 0 0 0 0 0 r10 0 0 p∗1 0 0 r20 0 0 0 p∗2 0 r30 0 0 0 0 0 1

·

n1,t−1

n2,t−1

n3,t−1

n∗1,t−1

n∗2,t−1

n∗3,t−1

R

(Schmidbauer & Rosch, 1995)


Project 4:


A Leslie-type model with two populations.

nc1,t

nc2,t

nc3,t

n∗c1,t

n∗c2,t

n∗c3,t

nv1,t

nv2,t

nv3,t

n∗v1,t

n∗v2,t

n∗v3,t

=

♣ ♣ ♣ ♣ ♣ ♣ 0 0 0 0 0 0♠ 0 0 0 0 0 0 0 0 0 0 00 ♠ 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 ♣ ♣ ♣ ♣ ♣ ♣0 0 0 ♠ 0 0 ♠ 0 0 ♠ 0 00 0 0 0 ♠ 0 0 ♠ 0 0 ♠ 00 0 0 0 0 0 ♣ ♣ ♣ ♣ ♣ ♣0 0 0 0 0 0 ♠ 0 0 0 0 00 0 0 0 0 0 0 ♠ 0 0 0 0♣ ♣ ♣ ♣ ♣ ♣ 0 0 0 0 0 0♠ 0 0 ♠ 0 0 0 0 0 ♠ 0 00 ♠ 0 0 ♠ 0 0 0 0 0 ♠ 0

·

nc1,t−1

nc2,t−1

nc3,t−1

n∗c1,t−1

n∗c2,t−1

n∗c3,t−1

nv1,t−1

nv2,t−1

nv3,t−1

n∗v1,t−1

n∗v2,t−1

n∗v3,t−1


Project 4:


Turkey: Long-run growth and urbanization.

mv

mc

0.75 0.8

0.85

0.9

0.95

1

1.0

5

1.1

1.1

5

1.2

1.2

5

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

mv

mc

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0


Project 5:

OPEC Announcements and Oil Price Volatility

Crude oil prices and OPEC announcements.

• Impact of OPEC announcements on crude oil prices?

• Impact on the distribution of daily returns, in particular:

– on the expectation of daily returns?– on the variance of daily returns?

• What can be said about expectation and volatility. . .

– right before an announcement will be made

(anticipation of the announcement),

– right after an announcement has been made

(aftereffect of the announcement)?


Project 5:


The WTI price series and OPEC announcements.

050

100

150

US

D/b

arre

l

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

cut

maintain

increase


Project 5:


The daily WTI return series and OPEC announcements.

−30

−20

−10

010

2030

daily

ret

urn

in p

erce

nt

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

cut

maintain

increase


Project 5:


Regression: conditional expectation; GARCH: conditional variance.

rt = c+∑s≥1

asrt−s +∑i

bidit + εt, (4)

εt = νt ·√ht, (5)

ht = α0 + α1ε2t−1 + βht−1 +

∑i

γidit. (6)

• (rt): series of daily returns on WTI crude oil price

• (dit): (modified) dummy variables for announcements of kind i

• (νt): Gaussian white noise with var(νt) = 1

• bi, γi: parameters (impact of an announcement of kind i)


Project 5:


Summary: The optimal model structure.

expectation volatility

cut● ● ● ● ● ●

● ●

● ● ● ● ● ● ● ●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9

● ●●

●

●

● ●

● ● ● ● ● ● ● ● ●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9

increase● ● ● ● ● ● ● ●

● ● ● ● ●

●

●●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9

maintain● ● ● ● ● ● ●

●

● ● ● ● ● ● ● ●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9● ● ●

●

●

●

● ● ● ● ● ● ● ● ● ●0.0

0.5

1.0

ta −− 6 ta −− 3 ta ta ++ 3 ta ++ 6 ta ++ 9


Project 5:



Research.

The scientific journal list relevant for Turkey:

http://www.ulakbim.gov.tr/cabim/ubyt/dergilist.php


http://www.ulakbim.gov.tr/cabim/ubyt/dergilist.php

Documents

EC 613: Advanced Topics in Financial Econometrics[1.4cm ... · 9/27/2012 · Angi R osch angi at angi-stat dot com The slides were produced using LATEX and R (the R project; website: